Big data refers to datasets that are large and complex in scale, and the size of big data may be relatively large in the order of PB (petabyte), EB (exabyte) or ZB (zettabyte). Therefore, backup of big data can be a time consuming operation, and the time for backup of big data is found to have a linear relationship with the size of big data. For example, if the backup speed is 20 MBs (megabytes) per second, a backup of a file system of 12 TBs (terabytes) will take at least up to 7 days to complete.
Typically for enterprise-level customers, the customers follow in most cases a backup policy of performing a full backup over the weekend, and performing incremental backups every work-day. If the backup of the enterprise data cannot be finished in this fixed backup window, it may have a serious impact on the enterprise's business or operations. In addition, when the data is lost or destroyed, customers have to restore data from the storage locations of the backup data. Similar to backup of big data, restoration of big data is also a time consuming operation. However, once the customers have to restore the data, they always desire to restore data at the earliest possible instance.